Triple
T28494880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cher |
E721079
|
entity |
| Predicate | usesCase |
P178290
|
FINISHED |
| Object | no |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: no | Statement: [Cher, usesCase, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCase Context triple: [Cher, usesCase, no]
-
A.
usesCaseSystem
Indicates that one entity employs or operates using a particular case system (e.g., grammatical or structural case-marking system).
-
B.
usedInCase
Indicates that something (such as an item, method, or piece of information) is employed or applied within a particular case or instance.
-
C.
usesCaseHarmony
Indicates that one element selects or governs another element such that their grammatical cases are compatible or harmonized according to the language’s case system.
-
D.
usesCaseManagementSystem
Indicates that an entity makes use of a case management system to organize, track, or handle cases or workflows.
-
E.
usesLawTo
Indicates that one entity applies or relies on a specific law as a means or tool to affect, regulate, or influence another entity or situation.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70e854b9c8190a3416e2189e17742 |
completed | May 3, 2026, 8:59 a.m. |
Created at: April 28, 2026, 3:03 a.m.